AI Inspection
AI Vision Inspection
Automated quality inspection, defect detection and visual process control for the production line.
Overview
AI Vision Inspection
A complete industrial computer-vision platform — not a collection of scripts. Capture samples, label defects, train a model, deploy to the edge, hand pass/fail to the PLC and store the evidence. Every result is fed back into PacketDCS OEE so quality loss becomes measurable.
<1sinspection cycle
24/7consistent grading
100%traceable evidence
Capabilities
What the product does
Defect & anomaly detection
Surface, scratch, contamination and anomaly detection where fixed rules break down.
Classification & segmentation
Object detection, instance and semantic segmentation, golden-sample comparison.
Presence & assembly verification
Confirm components, orientation, seals and completeness before the next station.
OCR, barcode & QR
Read date codes, lot numbers, serials and 1D/2D codes for full traceability.
Dimensional & colour checks
Measurement tools, colour and texture analysis, count and pass/fail logic.
PLC pass/fail handshake
Map results to reject actuators over TCP/IP, Modbus and digital I/O.
How it works
Workflow
Camera triggerImage acquisitionPre-processingRegion of interestAI inspection modelMeasurement / OCR / logicPass–fail decisionPLC outputEvidence storage
Integration
- TCP/IP & Modbus TCP/RTU
- OPC UA & MQTT
- Digital I/O reject control
- GenICam industrial cameras
- Operator review & false-call correction
- Model versioning, rollback & drift monitoring
Into OEE
Vision alone tells you a unit failed. PacketDCS tells you why — correlating every reject with machine state, recipe, temperature, speed and operator, so quality losses roll straight into device-level OEE.
Case studies
Where it is deployed
Proof of concept in progress
AI Dress-Bird Grading — Poultry Processing
A poultry processor grades every dressed bird on the shackle line against a documented quality standard — Grade A, B, C or reject — covering torn skin, scratch skin, haematoma and bruising, broken parts (patah), ammonia burn and other defect classes. PacketDCS is running a proof of concept on this line: AI vision grading every bird as it moves, at line speed, with per-bird evidence — measured against the graders it is meant to support.
Read the case study
Solution capability
Bottle Cap Defect & Date-Code OCR
A high-speed beverage line needs every cap checked for seating and damage, and every date code read and verified — at full line rate.
Read the case study
Solution capability
PCB Assembly Verification
Verify component presence, polarity and orientation on populated boards before they reach reflow and test.
Read the case study
Next step
Evaluate AI Vision Inspection
A structured, paid proof of concept on your own line, with quantified results.